Go for science?

This page summarizes the projects mentioned and recommended in the original post on /r/golang

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  • awesome-scientific-go

    Go libraries for scientific computing

  • Maybe here is some help with the libraries: https://github.com/samuell/awesome-scientific-go

  • hep

    hep is the mono repository holding all of go-hep.org/x/hep packages and tools

  • Have a look at go-hep https://go-hep.org/

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • gonum

    Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more

  • You should check out this https://github.com/gonum/gonum

  • tdaq

    tdaq: a toolkit for building DAQ systems

  • npyio

    npyio provides read/write access to numpy data files.

  • https://github.com/sbinet/npyio (r/w NumPy Array data files)

  • Apache Arrow

    Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing

  • https://github.com/apache/arrow (r/w Arrow files/streams)

  • fitsio

    fitsio is a pure-Go package to read and write `FITS` files

  • https://github.com/astrogo/fitsio (r/w FITS files for astronomy)

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • boostio

    Serialization library compatible with C++ Boost Serialization

  • https://github.com/go-boostio/boostio (r/w compatibility w/ Boost.Serialization, for binary streams, XML ones are still a WIP)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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